An Option-Based Operational Risk Management on Pandemics

In this paper, we employ the theory of real option pricing to address problems in the area of operational risk management. Particularly, we develop a two-stage model to help firms determine the optimal triggers in the event of an influenza pandemic. In the first stage, we propose a regime-dependent epidemic model to simulate the spread of the virus, depending on whether the firm is active or inactive. In the second stage, we view the reactivation decision as a call option and the suspension decision as a put option, and use dynamic programming method to determine the optimal switching thresholds. Our numerical experiments suggest that given the parameter values in our paper, it is optimal for the firm to suspend the business (or parts of its business) when the fraction of infected employees is higher than 18%, and to reactivate the operation anytime the fraction drops to 3%. When considering the uncertainty in the future, firms are more conservative about the decisions of suspension and reactivation. If the firm incurs switching costs, the suspension threshold increases with costs, while the reactivation threshold decreases with costs. By implementing policies to control the disease, firms can meet their social obligations and in the meantime, increase their values in both regimes.